Optimization chromatographic response

For manual optimization methods the peak separation function, P, is easy to determine and can be calculated as shown in Figure 4.30 (479). The chromatographic response function for the chromatogram is then simply the sum of the In P values for the n adjacent peak pairs. 

A simple and efficient alternative to the traditional UV detection of amino acids and related compounds is nowadays represented by the evaporative light scattering (ELS) detector, which allows the direct chromatographic separation, with no need for preliminary derivatization. In the field of glycopeptides-based CSPs, it was applied for the first time in the chromatographic resolution of carnitine and 0-acylcarnitine enantiomers on a TE CSP [61]. The considered compounds are nonvolatile solids and gave optimal ELS response under a variety of experimental conditions (buffered and unbuffered mobile phases, flow-rates from 0.5 to 1.5 mL/min, different kind and... 

Chromatographic response and optimization functions Experimental variables Optimization method Ref... 

Simplex Optimization Criteria. For chromatographic optimization, it is necessary to assign each chromatogram a numerical value, based on its quality, which can be used as a response for the simplex algorithm. Chromatographic response functions (CRFs), used for this purpose, have been the topics of many books and articles, and there are a wide variety of such CRFs available (33,34). The criteria employed by CRFs are typically functions of peak-valley ratio, fractional peak overlap, separation factor, or resolution. After an extensive (but not exhaustive) survey, we... 

Optimization Criteria for Interpretive Methods. As noted earlier in our discussion of the simplex methods, there are many chromatographic response functions (CRFs) for the evaluation and comparison of chromatograms during an optimization process. Here we discuss two CRFs that we employed successfully with this interpretive method of optimization. Since the retention behavior of every solute must be modeled prior to optimization, the number of sample components is known beforehand it is thus unnecessary to include the number of peaks in these CRFs as was done in CRF-3 (equation 8) for the simplex. 

In the literature many different terms are used for such criteria (chromatographic) response functions, objective functions or (chromatographic) optimization functions. Throughout the rest of this chapter, the neutral term optimization criteria will be used. 

Optimization or experimental design software packages for modeling the chromatographic response as a function of one or more method variables. These can also play a key role in data management of the considerable information that results from rigorous method development exercises. 

Selectivity in HPLC is obtained by setting optimal chromatographic conditions, such as mobile phase composition, column temperature, and detector wavelength. There are a variety of ways to validate selectivity. One approach is to demonstrate a lack of response in the blank biological matrix. A second approach is to check whether the intercept of the calibration curve is significantly different from zero. 

It has also proven advantageous to use a combination of individual responses in order to optimize as many parameters as possible (39-43). The two performance goals for a separation of bisphenols by MEKC were good resolution among five peaks and short total analysis time (42). Thus, a chromatographic response function (CRF) was employed that was a product of two types of desirability functions, as used by Divjak et al. (30-33, 44). Resolution (R) between two adjacent peaks in an electropherogram was calculated using... 

FIGURE 5.2. Representative electropherograms for three of the experiments of a Box-Behnken design and corresponding CRF (chromatographic response function) values. Used to optimize a separation of Bisphenols E, A, AP, and P, and Tetramethyl bisphenol A. Extracted from Reference 42. 

Different aggregations of objective criteria have been developed for particular analytical methods. Table 4.2 gives examples of objective functions for chromatography and spectroscopy. The objective function for chromatography, the chromatographic response function (CRF) accounts for all m peaks of the chromatogram, the time t for elution of the last peak, the noise, Af , at the measurement point of peak i, and the selectivity of peak separation based on Kaiser s measure for peak separation fig (see Figure 4.5). For optimal separations, the CRF is maximized. 

Planar response function (PRF) has been used in the statistical approach to solvent selectivity [40] that is a modified form of the chromatographic response function (CRF) used by Morgan and Deming in GC optimization studies [42]. PRF is defined by... 

Reliable flame photometric detector quantification of organosulphur compounds requires careful optimization of the gas chromatograph parameters. Although the relative response of the flame photometric detector to various sulphur compounds remains somewhat controversial [7], analysis of organosulphur compounds by flame photometric detector is now relatively straightforward. 

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